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--- |
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library_name: transformers |
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language: |
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- ar |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper tiny AR - BH |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper tiny AR - BH |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on the quran-ayat-speech-to-text dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0171 |
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- Wer: 0.1132 |
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- Cer: 0.0409 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 15 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 0.0145 | 1.0 | 219 | 0.0160 | 0.1213 | 0.0455 | |
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| 0.0115 | 2.0 | 438 | 0.0123 | 0.1267 | 0.0469 | |
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| 0.0082 | 3.0 | 657 | 0.0112 | 0.1157 | 0.0399 | |
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| 0.0061 | 4.0 | 876 | 0.0111 | 0.1173 | 0.0406 | |
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| 0.0056 | 5.0 | 1095 | 0.0116 | 0.1137 | 0.0389 | |
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| 0.0062 | 6.0 | 1314 | 0.0122 | 0.1117 | 0.0367 | |
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| 0.0021 | 7.0 | 1533 | 0.0129 | 0.1166 | 0.0396 | |
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| 0.0028 | 8.0 | 1752 | 0.0136 | 0.1167 | 0.0385 | |
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| 0.0017 | 9.0 | 1971 | 0.0141 | 0.1140 | 0.0370 | |
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| 0.0017 | 10.0 | 2190 | 0.0148 | 0.1119 | 0.0381 | |
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| 0.0012 | 11.0 | 2409 | 0.0152 | 0.1117 | 0.0366 | |
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| 0.0013 | 12.0 | 2628 | 0.0156 | 0.1122 | 0.0373 | |
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| 0.0008 | 13.0 | 2847 | 0.0159 | 0.1120 | 0.0377 | |
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| 0.0011 | 14.0 | 3066 | 0.0171 | 0.1128 | 0.0408 | |
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| 0.0008 | 15.0 | 3285 | 0.0161 | 0.1108 | 0.0369 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.19.1 |
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